The invention relates to computing quantization values used for encoding coeffients of a digital image or video frame and more particularly to optimizing the computed quantization values to reduce distortion in the digital image or video frame when encoding is performed with a limited number of bits.
In many of today's image and video coders, the quality of encoded images is controlled by selecting one or more quality parameters. Block-based image and video coders, use a parameter known as a quantization scale or step for each block of pixels in the image. The quantization steps are used for scaling pixel values within the same step ranges to the same values. Image blocks encoded with the same quantization scale have approximately the same quality. The number of bits needed for encoding an image depends on desired image quality (quantization scales) and on the inherent statistics of the image. As a result, different images encoded with the same scales (same image quality) will occupy a different number of bits.
In many applications, the number of bits available for encoding one or several frames is fixed in advance, and some technique is necessary to select the quantization scales that will produce that target number of bits and encode the video frames with the highest possible quality. For example, in a digital video recording, a group of frames (GOP) must occupy the same number of bits for an efficient fast-forward/fast-rewind capability. In video telephony, the channel rate, communication delay, and size of encoder buffers determine the available number of bits for one or more frames.
Existing quantizer or buffer control methods are classified into three major types. A first type of quantizer control method encodes each image block several times with a set of quantization scales. The number of bits produced for each case is measured and a scale for each block is smartly selected so the sum of the bits for all combined blocks hits the desired target bit number. The first type of quantizer control techniques cannot be used for real-time encoding because of the high computational complexity required to encode each image block multiple times.
The first type of quantizer control is described in the following publications: K. Ramchandran, A. Ortega, and M. Vetterli, "Bit Allocation for Dependent Quantization with Applications to Multi-Resolution and MPEG Video Coders," IEEE Trans. on Image Processing, Vol. 3, N. 5, pp. 533-545, September 1994; W. Ding and B. Liu, "Rate Control of MPEG Video Coding and Recording by Rate-Quantization Modeling," IEEE Trans. on Circuits and Systems for Video Technology, Vol. 6, N. 1, pp. 12-19, February 1996; and L. J. Lin, A. Ortega, and C. C. J. Kuo, "Rate Control Using Spline-interpolated R-D Characteristics," Proc. of SPIE Visual Communications and Image Processing, pp. 111-122, Orlando, Fla., March 1996.
A second type of quantizer control technique measures the number of bits spent in previously encoded image blocks and measures other parameters such as, buffer fullness, block activity, etc. These measurements are used to select the quantization scale for the current block. The second type of quantizer control is popular for real-time encoding because of its low computational complexity. However, the second type of quantizer control is inaccurate in achieving the target number of bits and must be combined with additional encoding techniques to avoid bit or buffer overflow and underflow.
The second method is described in the following publications: U.S. Pat. No. 5,038,209 entitled "Adaptive Buffer/Quantizer Control for Transform Video Coders", issued Aug. 6, 1991 to H. M. Ming; U.S. Pat. No. 5,159,447 entitled "Buffer Control for Variable Bit-Rate Channel", issued Oct. 27, 1992 to B. G. Haskell and A. R. Reibman; and U.S. Pat. No. 5,141,383 entitled "Pseudo-Constant Bit Rate Video Coding with Quantization Parameter Adjustment", issued Aug. 31, 1993 to C. T. Cheng and A. H. Wong.
A third type of quantizer control technique uses a model to predict the number of bits needed for encoding the image blocks. The quantizer model includes the blocks' quantization scales and other parameters, such as, block variances. The quantization scales are determined by some mathematical optimization of the encoder model. The third type of quantizer control is computationally simple and can be used in real-time, but is highly sensitive to model errors and often produces inaccurate results.
The third type of quantizer control technique is described in the following publications. E. D. Frimout, J. Biemond, and R. L. Lagendik, "Forward Rate Control for MPEG Recording," Proc. of SPIE Visual Communications and Image Processing, Cambridge, Mass., pp. 184-194, November 1993; U.S. Pat. No. 5,323,187 entitled, "Image Compression System by Setting Fixed Bit Rates", issued Jun. 21, 1994 to K. Park and A. Nicoulin, "Composite Source Modeling for Image Compression," Ph.D. Thesis N. 1444 (1995), Ecole Polytechnique Federale de Lausanne, Chapter 6, 1995.
Thus, a need remains for improving the image quality of quantized image or video frames while reducing the time and computational complexity required to generate optimized quantization values.